This application relates to content identification.
Online social networks have become popular for professional and/or social networking. Some online social networks provide content items that may be of interest to users, e.g., digital advertisements targeted to a user, or identification of other users and/or groups that may of interest to a user. The content items can, for example, be selected based on content of a user account, e.g., based on keywords identified from a crawl of a user's page. Such content item identification schemes, however, may not identify optimum content items if the user page includes only short, ambiguous messages, misspelled words, or is primarily non-textual content, e.g., photograph collections, that present unique challenges for machine-based relevance analysis.
Additionally, such content identification schemes do not readily facilitate advertiser targeting of publishers that may have a broad range of visiting users, e.g., social networks. For example, social networking sites have users that have many different interests, and thus advertisers may not readily identify particular verticals for the social networking site. Accordingly, some of the content items, e.g., advertisements directed to particular products, may not be of interest to many users of an online social network.